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NEW 🚨 Inside Anthropic — AGI, AI Optimism, Regulatory Capture, Open Source & More! Joe Lonsdale sits down with Anthropic's Sholto Douglas and Nicholas Marwell - Have we reached AGI — and what does it mean? - What are the most exciting breakthroughs at Anthropic right now? - What...

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American Optimist

18,750 subscribers

225,104 次观看 • 29 天前 •via X (Twitter)

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American Optimist 的头像
American Optimist29 天前

@_sholtodouglas @the_marwell Get new episodes straight to your inbox:

flet4fletcher 的头像
flet4fletcher29 天前

@JTLonsdale @_sholtodouglas @the_marwell Anthropic are left wing crooks that cannot be trusted, and neither should Palantir for enabling them through endorsement.

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Doug Standley29 天前

@JTLonsdale @_sholtodouglas @the_marwell Can’t wait to listen to this!

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My biggest fear for AI is concentration of power. Open-source is a solution. Watch this video to understand what's going on: 0:00 Intro 0:52 NVIDIA's letter 1:36 What is open-source? 3:53 How open-source works 5:48 Kimi K3 6:38 Closed vs Open 8:39 Open-source in the U.S. 12:10 The AI stack 13:05 What if open source wins? 14:08 Jevon's Paradox 14:56 How the AI stack is affected 18:04 User experience 19:38 AI safety 30:30 China 35:50 Distillation 41:40 Banning Chinese models? 43:38 Anthropic's response
53:37

My biggest fear for AI is concentration of power. Open-source is a solution. Watch this video to understand what's going on: 0:00 Intro 0:52 NVIDIA's letter 1:36 What is open-source? 3:53 How open-source works 5:48 Kimi K3 6:38 Closed vs Open 8:39 Open-source in the U.S. 12:10 The AI stack 13:05 What if open source wins? 14:08 Jevon's Paradox 14:56 How the AI stack is affected 18:04 User experience 19:38 AI safety 30:30 China 35:50 Distillation 41:40 Banning Chinese models? 43:38 Anthropic's response

Matthew Berman

13,839 次观看 • 3 个月前

EPISODE 142: Understanding the AI Wave Joe Lonsdale sits down with 8VC Partners Alex Kolicich & Jack Moshkovich Why is AI fundamentally disruptive? What does it mean for large software incumbents? Will LLMs become commodities? And are we entering a bubble, or just getting started? (00:00) Episode intro (01:40) Smart enterprise thesis (04:00) Did enterprise software dramatically boost productivity? (08:30) Understanding the AI wave (11:45) Will LLMs become commodities? (17:10) OpenAI vs Anthropic vs Meta vs Grok (20:30) Frontier models vs enterprise incumbents (25:27) What did Palantir get right? (32:30) AI case studies/new possibilities (43:00) The most surprising aspect of the AI wave (46:12) Are we entering a bubble? Or just getting started? (52:40) Biggest concern with AI (58:00) Biggest reason for optimism
1:01:18

EPISODE 142: Understanding the AI Wave Joe Lonsdale sits down with 8VC Partners Alex Kolicich & Jack Moshkovich Why is AI fundamentally disruptive? What does it mean for large software incumbents? Will LLMs become commodities? And are we entering a bubble, or just getting started? (00:00) Episode intro (01:40) Smart enterprise thesis (04:00) Did enterprise software dramatically boost productivity? (08:30) Understanding the AI wave (11:45) Will LLMs become commodities? (17:10) OpenAI vs Anthropic vs Meta vs Grok (20:30) Frontier models vs enterprise incumbents (25:27) What did Palantir get right? (32:30) AI case studies/new possibilities (43:00) The most surprising aspect of the AI wave (46:12) Are we entering a bubble? Or just getting started? (52:40) Biggest concern with AI (58:00) Biggest reason for optimism

American Optimist

417,594 次观看 • 8 个月前

New Delphi Podcast with TravisGood, co-founder of ambient.xyz Travis believes open source AI will win and that OpenAI and Anthropic are making a major strategic mistake by betting against it We discuss – Why closed AI providers can’t be trusted as infrastructure – China’s open source advantage – What happens if OpenAI reaches AGI – Prompt injection and AI’s unsolved safety problem – The AI CapEx bubble and a possible AI winter – How Ambient is building Uber for inference - 00:00 Intro - 03:20 What Ambient Is and How It Works - 18:40 Verified AI Inference - 40:20 China and the Open-Source AI Race - 49:00 Why Closed AI Is Making a Mistake - 1:03:00 What Happens If OpenAI Reaches AGI? - 1:17:10 The AI Bubble and a Possible AI Winter
1:32:00

New Delphi Podcast with TravisGood, co-founder of ambient.xyz Travis believes open source AI will win and that OpenAI and Anthropic are making a major strategic mistake by betting against it We discuss – Why closed AI providers can’t be trusted as infrastructure – China’s open source advantage – What happens if OpenAI reaches AGI – Prompt injection and AI’s unsolved safety problem – The AI CapEx bubble and a possible AI winter – How Ambient is building Uber for inference - 00:00 Intro - 03:20 What Ambient Is and How It Works - 18:40 Verified AI Inference - 40:20 China and the Open-Source AI Race - 49:00 Why Closed AI Is Making a Mistake - 1:03:00 What Happens If OpenAI Reaches AGI? - 1:17:10 The AI Bubble and a Possible AI Winter

Tommy

24,634 次观看 • 3 个月前

POD UP 🚨 Besties are back! -- The Fight Over Open Source AI -- Chinese Distillation -- Anthropic's $1.5B Settlement -- $GOOG and $TSLA Drop on Surging AI Capex -- Socialism Corner: Evictions = Violence and the Slow Encroachment on Private Property Rights (0:00) Bestie intros! (0:18) The fight to save open source AI: Kimi K3 panic, Anthropic/OpenAI regulatory capture (27:38) Anthropic/OpenAI historic growth rates, China's long game (48:29) Anthropic's $1.5B piracy settlement and the great IP theft hypocrisy (1:07:12) Google and Tesla stocks tank on surging AI capex (1:17:19) Socialism Corner: "Evictions = Violence" and the threat to private property rights
1:33:43

POD UP 🚨 Besties are back! -- The Fight Over Open Source AI -- Chinese Distillation -- Anthropic's $1.5B Settlement -- $GOOG and $TSLA Drop on Surging AI Capex -- Socialism Corner: Evictions = Violence and the Slow Encroachment on Private Property Rights (0:00) Bestie intros! (0:18) The fight to save open source AI: Kimi K3 panic, Anthropic/OpenAI regulatory capture (27:38) Anthropic/OpenAI historic growth rates, China's long game (48:29) Anthropic's $1.5B piracy settlement and the great IP theft hypocrisy (1:07:12) Google and Tesla stocks tank on surging AI capex (1:17:19) Socialism Corner: "Evictions = Violence" and the threat to private property rights

The All-In Podcast

285,545 次观看 • 3 个月前

ARC-AGI is redefining how to measure progress on the path to AGI - focusing on reasoning, generalization, and adaptability instead of memorization or scale. At NeurIPS 2025, YC's Diana sat down with ARC Prize President Greg Kamradt to find out why most AI benchmarks fail, how ARC-AGI reveals the limits of today’s models, and why measuring intelligence may be harder than building it. 00:11 — What ARC Prize is and why it exists 00:38 — François Chollet’s definition of AGI 01:48 — What ARC-AGI Actually Tests 02:25 — When LLMs Failed the ARC Benchmark 03:38 — ARC-AGI Becomes the Standard 04:49 — False Positives in AI Progress 06:06 — The Evolution of ARC-AGI 08:55 — Measuring Intelligence beyond just accuracy 10:25 — What happens if a model solves ARC-AGI?
11:59

ARC-AGI is redefining how to measure progress on the path to AGI - focusing on reasoning, generalization, and adaptability instead of memorization or scale. At NeurIPS 2025, YC's Diana sat down with ARC Prize President Greg Kamradt to find out why most AI benchmarks fail, how ARC-AGI reveals the limits of today’s models, and why measuring intelligence may be harder than building it. 00:11 — What ARC Prize is and why it exists 00:38 — François Chollet’s definition of AGI 01:48 — What ARC-AGI Actually Tests 02:25 — When LLMs Failed the ARC Benchmark 03:38 — ARC-AGI Becomes the Standard 04:49 — False Positives in AI Progress 06:06 — The Evolution of ARC-AGI 08:55 — Measuring Intelligence beyond just accuracy 10:25 — What happens if a model solves ARC-AGI?

Y Combinator

98,369 次观看 • 10 个月前

My conversation with OpenAI co-founder Greg Brockman This is the most detailed first-person account of the 72 hours after Sam Altman was fired. We also go deep on what comes next: the global race to AGI, why ChatGPT stopped showing reasoning, how much of OpenAI's own code is now written by AI ("it's hard to know what percent is not"), and the untold story of how OpenAI actually started in 2015. 00:00:00 Introduction 00:00:49 Meeting Sam Altman and Starting OpenAI 00:02:40 Building the Founding Team 00:04:25 DeepMind's Lead Over OpenAI 00:04:54 Changing OpenAI to a For-Profit Model 00:06:05 Breakthrough Moments at OpenAI 00:08:22 What Dota 2 Meant for OpenAI 00:10:04 Reasoning Versus Prediction 00:11:59 Tensions Grow at OpenAI 00:15:44 Sam Altman's Firing 00:17:49 Greg Quits OpenAI 00:19:56 Sam Explores Deal with Microsoft's Satya 00:20:28 Petition for Altman's Return 00:23:43 Ilya Sutskever Leaves OpenAI 00:24:59 Lessons Learned after Sam Ousting 00:28:22 The Thing Ilya Said that Greg Can't Forget 00:32:22 Is AI Going Parabolic? 00:33:24 How Much of OpenAI's Code is Written by AI? 00:36:21 Do AI Chatbots Tell Us What We Want to Hear? 00:38:06 The Global AI Race to Reach AGI 00:38:40 What Happens if US Doesn't Reach AGI First? 00:39:49 Are Countries Stealing AI Advancements? 00:40:38 Why ChatGPT No Longer Shows Reasoning 00:41:47 The Finite Constraints of Compute 00:43:38 On Investing Early in Data Centers 00:46:31 The Future of Data Center Specialization 00:47:52 How to Decide Whose Queries to Serve 00:49:08 OpenAI on Consumer vs Enterprise Models 00:53:05 Data Centers in Space? 01:00:56 What Should AI Regulation Look Like? 01:04:33 The Future of AI-Powered Entrepreneurship 01:04:44 AI and Job Loss 01:07:15 The Skills Young People Should Invest In 01:11:30 What Does Success Look Like For You? Full episode on X below. Also find it on: • YouTube: • Spotify: • Apple:
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My conversation with OpenAI co-founder Greg Brockman This is the most detailed first-person account of the 72 hours after Sam Altman was fired. We also go deep on what comes next: the global race to AGI, why ChatGPT stopped showing reasoning, how much of OpenAI's own code is now written by AI ("it's hard to know what percent is not"), and the untold story of how OpenAI actually started in 2015. 00:00:00 Introduction 00:00:49 Meeting Sam Altman and Starting OpenAI 00:02:40 Building the Founding Team 00:04:25 DeepMind's Lead Over OpenAI 00:04:54 Changing OpenAI to a For-Profit Model 00:06:05 Breakthrough Moments at OpenAI 00:08:22 What Dota 2 Meant for OpenAI 00:10:04 Reasoning Versus Prediction 00:11:59 Tensions Grow at OpenAI 00:15:44 Sam Altman's Firing 00:17:49 Greg Quits OpenAI 00:19:56 Sam Explores Deal with Microsoft's Satya 00:20:28 Petition for Altman's Return 00:23:43 Ilya Sutskever Leaves OpenAI 00:24:59 Lessons Learned after Sam Ousting 00:28:22 The Thing Ilya Said that Greg Can't Forget 00:32:22 Is AI Going Parabolic? 00:33:24 How Much of OpenAI's Code is Written by AI? 00:36:21 Do AI Chatbots Tell Us What We Want to Hear? 00:38:06 The Global AI Race to Reach AGI 00:38:40 What Happens if US Doesn't Reach AGI First? 00:39:49 Are Countries Stealing AI Advancements? 00:40:38 Why ChatGPT No Longer Shows Reasoning 00:41:47 The Finite Constraints of Compute 00:43:38 On Investing Early in Data Centers 00:46:31 The Future of Data Center Specialization 00:47:52 How to Decide Whose Queries to Serve 00:49:08 OpenAI on Consumer vs Enterprise Models 00:53:05 Data Centers in Space? 01:00:56 What Should AI Regulation Look Like? 01:04:33 The Future of AI-Powered Entrepreneurship 01:04:44 AI and Job Loss 01:07:15 The Skills Young People Should Invest In 01:11:30 What Does Success Look Like For You? Full episode on X below. Also find it on: • YouTube: • Spotify: • Apple:

Shane Parrish

450,952 次观看 • 6 个月前

NEW🚨 Inside the Company That Evaluates AI Labs; Who Will Reach Recursive Self-Improvement First? Joe Lonsdale & Vivek Gopalan sit down with Rayan Krishnan, founder & CEO of Vals AI They cover: - How Rayan used Fable to solve a 370-year-old cipher - The science behind model evaluation / can you stay ahead of the labs? - Should labs self-regulate? What's the role for independent evaluators? - Which lab will reach RSI first — and what happens next? - How do models try to deceive evaluators? Episode 167 out now! (00:00) Episode intro (02:00) Palantir, Machiavelli & lessons from Alex Karp (07:50) Solving a 370-year-old cipher / Is AI making new discoveries? (12:10) How do you measure AI abilities across finance, legal, etc? (15:30) What is the science behind model evaluation? (18:00) The importance of independent evaluation (23:35) Evaluating Chinese models & addressing distillation (26:45) Will Anthropic reach Recursive Self-Improvement first? What happens next? (28:30) How do models try to deceive evaluators (33:00) Why Rayan remains optimistic about AI
36:58

NEW🚨 Inside the Company That Evaluates AI Labs; Who Will Reach Recursive Self-Improvement First? Joe Lonsdale & Vivek Gopalan sit down with Rayan Krishnan, founder & CEO of Vals AI They cover: - How Rayan used Fable to solve a 370-year-old cipher - The science behind model evaluation / can you stay ahead of the labs? - Should labs self-regulate? What's the role for independent evaluators? - Which lab will reach RSI first — and what happens next? - How do models try to deceive evaluators? Episode 167 out now! (00:00) Episode intro (02:00) Palantir, Machiavelli & lessons from Alex Karp (07:50) Solving a 370-year-old cipher / Is AI making new discoveries? (12:10) How do you measure AI abilities across finance, legal, etc? (15:30) What is the science behind model evaluation? (18:00) The importance of independent evaluation (23:35) Evaluating Chinese models & addressing distillation (26:45) Will Anthropic reach Recursive Self-Improvement first? What happens next? (28:30) How do models try to deceive evaluators (33:00) Why Rayan remains optimistic about AI

American Optimist

33,645 次观看 • 5 天前

EPISODE 143: How to Build with AI in 2026 Joe Lonsdale sits down with JD Ross, co-founder of Opendoor & WithCoverage What are the newest possibilities with AI? What does it mean for legacy SaaS? And why is JD excited for young talent entering the workforce today? (00:00) Episode intro (01:28) JD's entrepreneurial journey (05:18) Wins and challenges at Opendoor / $OPEN meme stock moment (09:55) WithCoverage and upending insurance brokerage (13:11) Mimetic frameworks for entrepreneurs (15:45) How AI is changing the way companies are built (20:21) The impact of AI on existing SaaS (26:50) How to stop AI spam and imposters (31:27) How should young people prepare for AI era? (34:20) The new invention era / why AI levels the playing field
36:10

EPISODE 143: How to Build with AI in 2026 Joe Lonsdale sits down with JD Ross, co-founder of Opendoor & WithCoverage What are the newest possibilities with AI? What does it mean for legacy SaaS? And why is JD excited for young talent entering the workforce today? (00:00) Episode intro (01:28) JD's entrepreneurial journey (05:18) Wins and challenges at Opendoor / $OPEN meme stock moment (09:55) WithCoverage and upending insurance brokerage (13:11) Mimetic frameworks for entrepreneurs (15:45) How AI is changing the way companies are built (20:21) The impact of AI on existing SaaS (26:50) How to stop AI spam and imposters (31:27) How should young people prepare for AI era? (34:20) The new invention era / why AI levels the playing field

American Optimist

76,418 次观看 • 8 个月前

My conversation with Sam Altman (Sam Altman), CEO of OpenAI. We discuss: - Kimi, distillation, and open source - OpenAI's compute bets - The Hugging Face incident - What happens after AGI - Raising kids in an age of abundant intelligence - And much more Enjoy! TIMESTAMPS 0:00 Intro 4:10 The Race for Compute 14:24 A Sci-Fi Cyber Incident 16:14 The Promise and Risks of AGI 23:27 How AI Will Change Jobs 29:38 Sam’s Vision for a Personal AI 35:02 Robotics, ChatGPT, and What Comes Next 44:39 The Weight of Leading OpenAI 51:36 OpenAI’s Biggest Lessons
55:47

My conversation with Sam Altman (Sam Altman), CEO of OpenAI. We discuss: - Kimi, distillation, and open source - OpenAI's compute bets - The Hugging Face incident - What happens after AGI - Raising kids in an age of abundant intelligence - And much more Enjoy! TIMESTAMPS 0:00 Intro 4:10 The Race for Compute 14:24 A Sci-Fi Cyber Incident 16:14 The Promise and Risks of AGI 23:27 How AI Will Change Jobs 29:38 Sam’s Vision for a Personal AI 35:02 Robotics, ChatGPT, and What Comes Next 44:39 The Weight of Leading OpenAI 51:36 OpenAI’s Biggest Lessons

Patrick OShaughnessy

2,015,879 次观看 • 3 个月前

A year ago, the big three was OpenAI, Anthropic, and Google. Things have changed. Moonshot's Kimi K3 sits above Gemini on every composite benchmark, and it's open source in 10 days. New episode: what K3 reveals about frontier margins, model sizes, and who's actually still in the game. 00:11 Is Kimi K3 the Third Best Model? 04:04 Why Delay the Weights? 05:30 2.8T Parameters and Serving Constraints 06:48 Frontier Margins and the 3x Price Hike 11:10 New Architecture, What Comes Next 14:09 Will Open Source Catch Closed? 19:51 Built for Chinese Accelerators 22:57 The Harness Is the Product 28:49 We're Still Early
31:43

A year ago, the big three was OpenAI, Anthropic, and Google. Things have changed. Moonshot's Kimi K3 sits above Gemini on every composite benchmark, and it's open source in 10 days. New episode: what K3 reveals about frontier margins, model sizes, and who's actually still in the game. 00:11 Is Kimi K3 the Third Best Model? 04:04 Why Delay the Weights? 05:30 2.8T Parameters and Serving Constraints 06:48 Frontier Margins and the 3x Price Hike 11:10 New Architecture, What Comes Next 14:09 Will Open Source Catch Closed? 19:51 Built for Chinese Accelerators 22:57 The Harness Is the Product 28:49 We're Still Early

SemiAnalysis

122,313 次观看 • 3 个月前

What does it mean when an AI model is “open weights” and how is it different than “open source”? Welcome to the next episode of the Open Model Series with merve, Hugging Face AI/ML engineer & open-sourceress! Every week we will discuss open-source & open-weight AI: what it is, how it works, and how you can run them on your own compute. Episode 3 out next week; episode 1 linked below. Please leave all your questions about open-source & open-weight AI in the comments. This is a super important topic that is novel to most people, and it can be challenging to grasp - so your questions are shared with many others.
1:02

What does it mean when an AI model is “open weights” and how is it different than “open source”? Welcome to the next episode of the Open Model Series with merve, Hugging Face AI/ML engineer & open-sourceress! Every week we will discuss open-source & open-weight AI: what it is, how it works, and how you can run them on your own compute. Episode 3 out next week; episode 1 linked below. Please leave all your questions about open-source & open-weight AI in the comments. This is a super important topic that is novel to most people, and it can be challenging to grasp - so your questions are shared with many others.

Harper Carroll

32,624 次观看 • 2 个月前

. OpenLedger x : The full episode Our core contributor Ram sat down with Sreeram Kannan (founder ) to discuss verifiable AI, crypto's app problem, AI's trust problem and much more Check out the video below to learn more Timestamps: 00:00 Sreeram's introduction 00:29 How to build verification for AI systems 01:27 The Crypto and AI problem 03:10 Unstoppable AGI 05:08 What is Verifiable AI 06:05 The Verifiability Problem with Centralized AI 07:15 The current state of AI and its future 08:48 How humans are getting better at intelligence extraction 10:31 What is OpenLedger doing 11:50 Where LLMs fall short and how co-ordination helps 12:50 SLMs are already there 13:29 Crypto as an incentivisation mechanism 15:38 Apps with commitments, achieving product market fit 16:50 Existing examples of commitments in society 18:24 Investable AI 19:00 Data contributors as co-owner 21:30 The solution for the incentivisation problem 22:25 Explaining explainable AI 23:58 Trusting the trustless way 25:07 Data is the new oil 25:40 The idea of openledger is very crypto native 26:50 David v Goliath (in the data perspective) 28:03 What Eigen is working on 29:06 Making unstoppable verifiable AI practically possible 32:20 What Sreeram uses for productivity 33:30 Make Eigen Labs agentic 34:16 (community question) How Sreeram frames his prompts 36:08 (community question) What's the momentum driver for blockchain apps and what is Sreeram most excited about? (ZkTLS) 38:54 (community question) Where is attribution and verification really needed in AI?
39:43

. OpenLedger x : The full episode Our core contributor Ram sat down with Sreeram Kannan (founder ) to discuss verifiable AI, crypto's app problem, AI's trust problem and much more Check out the video below to learn more Timestamps: 00:00 Sreeram's introduction 00:29 How to build verification for AI systems 01:27 The Crypto and AI problem 03:10 Unstoppable AGI 05:08 What is Verifiable AI 06:05 The Verifiability Problem with Centralized AI 07:15 The current state of AI and its future 08:48 How humans are getting better at intelligence extraction 10:31 What is OpenLedger doing 11:50 Where LLMs fall short and how co-ordination helps 12:50 SLMs are already there 13:29 Crypto as an incentivisation mechanism 15:38 Apps with commitments, achieving product market fit 16:50 Existing examples of commitments in society 18:24 Investable AI 19:00 Data contributors as co-owner 21:30 The solution for the incentivisation problem 22:25 Explaining explainable AI 23:58 Trusting the trustless way 25:07 Data is the new oil 25:40 The idea of openledger is very crypto native 26:50 David v Goliath (in the data perspective) 28:03 What Eigen is working on 29:06 Making unstoppable verifiable AI practically possible 32:20 What Sreeram uses for productivity 33:30 Make Eigen Labs agentic 34:16 (community question) How Sreeram frames his prompts 36:08 (community question) What's the momentum driver for blockchain apps and what is Sreeram most excited about? (ZkTLS) 38:54 (community question) Where is attribution and verification really needed in AI?

OpenLedger

274,881 次观看 • 1 年前

Thariq Shihipar (Thariq) is an engineer on Anthropic’s Claude Code team I asked him how Anthropic makes the most out of the models for engineering and how the industry will change soon. In this episode: • Internal best practices in leveraging the models • What percent of Anthropic's work is fully autonomous • How Anthropic maintains higher volumes of code • What has worked in preventing AI-written breakages Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsor of this episode for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Chapters: 00:00 Intro 00:29 Onboarding at Anthropic 02:53 Internal capabilities vs external perception 06:16 Model vs Harness 08:55 What percent of Anthropics changes are fully autonomous 14:51 Computer use 17:42 How to make the most out of your compute 20:45 Loop engineering 22:47 Where the industry will go soon 26:02 Which model do Anthropic engineers use 27:38 Is learning a particular model worth it 30:56 Prompting tips for todays models 35:04 How to get the models to do tasteful work 39:00 How much of writing is done by AI at Anthropic 45:36 Code ownership and maintenance at Anthropic 52:04 How Anthropic prevents breakages 55:24 Visibility and sharing your work 58:42 Luck surface area example 01:00:57 Should people still learn to code 01:07:42 Advice for his younger self 01:09:58 Outro
1:10:54

Thariq Shihipar (Thariq) is an engineer on Anthropic’s Claude Code team I asked him how Anthropic makes the most out of the models for engineering and how the industry will change soon. In this episode: • Internal best practices in leveraging the models • What percent of Anthropic's work is fully autonomous • How Anthropic maintains higher volumes of code • What has worked in preventing AI-written breakages Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsor of this episode for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Chapters: 00:00 Intro 00:29 Onboarding at Anthropic 02:53 Internal capabilities vs external perception 06:16 Model vs Harness 08:55 What percent of Anthropics changes are fully autonomous 14:51 Computer use 17:42 How to make the most out of your compute 20:45 Loop engineering 22:47 Where the industry will go soon 26:02 Which model do Anthropic engineers use 27:38 Is learning a particular model worth it 30:56 Prompting tips for todays models 35:04 How to get the models to do tasteful work 39:00 How much of writing is done by AI at Anthropic 45:36 Code ownership and maintenance at Anthropic 52:04 How Anthropic prevents breakages 55:24 Visibility and sharing your work 58:42 Luck surface area example 01:00:57 Should people still learn to code 01:07:42 Advice for his younger self 01:09:58 Outro

Ryan Peterman

65,784 次观看 • 1 个月前

SPECIAL: How Erik Voorhees Built the Leading Private, Uncensored AI Venice Timestamps: 00:00 Intro & ShapeShift Origin Story 05:25 Did Crypto Play Out as Expected? 06:25 AI vs. Crypto: Are They Similar? 07:23 What Is Venice AI? 09:38 From ShapeShift to Venice 10:31 Censorship in AI & the Open Source Alternative 11:38 Hibachi, infiniFi Ads 12:00 Are AI Labs Too Censored? 13:24 Relay Ad 13:41 Geopolitics: Chinese Open Source vs. US Closed Models 14:15 SBF, the Anthropic Investment & Crypto Scammers 16:26 NearCon, Illia & the AI/Crypto Convergence
17:28

SPECIAL: How Erik Voorhees Built the Leading Private, Uncensored AI Venice Timestamps: 00:00 Intro & ShapeShift Origin Story 05:25 Did Crypto Play Out as Expected? 06:25 AI vs. Crypto: Are They Similar? 07:23 What Is Venice AI? 09:38 From ShapeShift to Venice 10:31 Censorship in AI & the Open Source Alternative 11:38 Hibachi, infiniFi Ads 12:00 Are AI Labs Too Censored? 13:24 Relay Ad 13:41 Geopolitics: Chinese Open Source vs. US Closed Models 14:15 SBF, the Anthropic Investment & Crypto Scammers 16:26 NearCon, Illia & the AI/Crypto Convergence

The Rollup

47,879 次观看 • 8 个月前

A new episode of Hivemind is out now! This week we discuss the market rebound, DeFi exploit fallout, Crypto AI resurgence, and more. Timestamps: 0:00 Intro + market sentiment shift 08:55 The Aave/KelpDAO exploit explained 17:00 Why DeFi lending models may need to change 37:30 Where DeFi yield still makes sense 38:00 USDAI and real-world AI infrastructure yield 48:20 Venice, Bittensor, and AI token narratives 54:00 How AI agents are changing productivity 1:00:50 What the team is watching next
1:07:53

A new episode of Hivemind is out now! This week we discuss the market rebound, DeFi exploit fallout, Crypto AI resurgence, and more. Timestamps: 0:00 Intro + market sentiment shift 08:55 The Aave/KelpDAO exploit explained 17:00 Why DeFi lending models may need to change 37:30 Where DeFi yield still makes sense 38:00 USDAI and real-world AI infrastructure yield 48:20 Venice, Bittensor, and AI token narratives 54:00 How AI agents are changing productivity 1:00:50 What the team is watching next

Delphi Digital

12,596 次观看 • 6 个月前

I spoke with Dan Ives about the AI trade and why it will be bigger than everyone thinks. He explains where value is accruing, why Dario’s warnings about AI are wrong, the White House AI meeting, the importance of sovereign AI, and his new Ives Ultra Fund. YouTube: Apple: Spotify: TIMESTAMPS: 0:00 - Intro 1:12 - Where's the value in the AI trade? 2:32 - Dario's AI warning & regulatory capture 5:15 - Are OpenAI & Anthropic in trouble? 11:04 - Trump's White House AI meeting 13:51 - Open source vs closed source AI 15:32 - Token price war & the Anthropic IPO 22:33 - How to invest in the AI trade 25:04 - Personal AI agents & consumer AI 26:31 - Why tech is ignoring macro headwinds 30:36 - The Ives Ultra AI Fund 33:21 - Data, sovereign AI & the future of work
40:38

I spoke with Dan Ives about the AI trade and why it will be bigger than everyone thinks. He explains where value is accruing, why Dario’s warnings about AI are wrong, the White House AI meeting, the importance of sovereign AI, and his new Ives Ultra Fund. YouTube: Apple: Spotify: TIMESTAMPS: 0:00 - Intro 1:12 - Where's the value in the AI trade? 2:32 - Dario's AI warning & regulatory capture 5:15 - Are OpenAI & Anthropic in trouble? 11:04 - Trump's White House AI meeting 13:51 - Open source vs closed source AI 15:32 - Token price war & the Anthropic IPO 22:33 - How to invest in the AI trade 25:04 - Personal AI agents & consumer AI 26:31 - Why tech is ignoring macro headwinds 30:36 - The Ives Ultra AI Fund 33:21 - Data, sovereign AI & the future of work

Anthony Pompliano 🌪

76,244 次观看 • 29 天前

Google DeepMind CEO Demis Hassabis says we’re in the ‘foothills of the singularity’ I sat down with him to talk about what that means, curing every disease, and human meaning post-AGI: 0:00 Intro 0:45 What Demis is most excited about at I/O 1:46 Have AGI timelines shifted? 3:30 What's still missing before AGI 6:50 AI curing every disease 9:19 What diseases get cured first? 10:50 What Demis works on after AGI 11:48 Human meaning after AGI 13:50 The human skills that get more valuable 15:19 What's underhyped in AI right now
16:40

Google DeepMind CEO Demis Hassabis says we’re in the ‘foothills of the singularity’ I sat down with him to talk about what that means, curing every disease, and human meaning post-AGI: 0:00 Intro 0:45 What Demis is most excited about at I/O 1:46 Have AGI timelines shifted? 3:30 What's still missing before AGI 6:50 AI curing every disease 9:19 What diseases get cured first? 10:50 What Demis works on after AGI 11:48 Human meaning after AGI 13:50 The human skills that get more valuable 15:19 What's underhyped in AI right now

Rowan Cheung

120,402 次观看 • 5 个月前

Marc Andreessen and Erik Torenberg went live on MTS to talk the hyperstition of AI Doomers, suicidal empathy, the AI Induced Psychosis Summit, push polls, UFOs and more. 00:00 - Intro 00:42 - The Anthropic Blackmail Incident & AI Doomer Literature 02:49 - Suicidal Empathy & the SPLC Indictment 16:33 - AI, Jobs & the Rise of the AI Vampire 25:39 - The Future of Tech Jobs: From Coder to Builder 30:55 - AI Psychosis, AI Cope & Why the Models Are Actually Great Now 38:48 - Why AI Sentiment Polls Are Misleading 45:28 - UFOs: What We Know and What the Government Has Hidden 52:25 - Advice for Young People & the Generational Divide Marc Andreessen 🇺🇸 Erik Torenberg
1:06:36

Marc Andreessen and Erik Torenberg went live on MTS to talk the hyperstition of AI Doomers, suicidal empathy, the AI Induced Psychosis Summit, push polls, UFOs and more. 00:00 - Intro 00:42 - The Anthropic Blackmail Incident & AI Doomer Literature 02:49 - Suicidal Empathy & the SPLC Indictment 16:33 - AI, Jobs & the Rise of the AI Vampire 25:39 - The Future of Tech Jobs: From Coder to Builder 30:55 - AI Psychosis, AI Cope & Why the Models Are Actually Great Now 38:48 - Why AI Sentiment Polls Are Misleading 45:28 - UFOs: What We Know and What the Government Has Hidden 52:25 - Advice for Young People & the Generational Divide Marc Andreessen 🇺🇸 Erik Torenberg

MTS

46,292 次观看 • 5 个月前

Context Rot! What is it? What does it mean? New video breaking down Chroma's latest paper and applying it to interacting with AI 00:00 - What is Context? 04:44 - The Flaw of "Needle in a Haystack" 10:22 - How Distractors Degrade AI Performance 14:31 - The Impact of Prompt Structure 25:55 - Why Unrelated Needles Are Easier to Find 31:02 - The Unreliability of Text Replication 37:03 - Actionable Takeaways for Better Prompting
40:35

Context Rot! What is it? What does it mean? New video breaking down Chroma's latest paper and applying it to interacting with AI 00:00 - What is Context? 04:44 - The Flaw of "Needle in a Haystack" 10:22 - How Distractors Degrade AI Performance 14:31 - The Impact of Prompt Structure 25:55 - Why Unrelated Needles Are Easier to Find 31:02 - The Unreliability of Text Replication 37:03 - Actionable Takeaways for Better Prompting

matt palmer

22,103 次观看 • 1 年前

EP:19 ft Ishank Gupta the co-founder of KGeN Foundation 🟩! Discussing: The benefits of travelling, how to navigate the stress of web3, solving distribution and much more! Timestamps: 2:00 What was life like before web3? 7:25 What lessons did you learn from travelling so much? 11:30 How has travelling impacted your perspective for business 14:45 Biggest lessons from working with some of the largest brands in the world. 20:00 What do you look like when hiring? 26:45 How do you navigate such a volatile market on a personal level? 32:55 Story of how KGEN started 40:00 How important is it when selecting which investors to work with. 43:30 What are the missing pieces to solving distribution for web3 gaming? 47:00 How do you re-engage users? 50:00 How does KGEN Chiefs work? 53:00 Aligning incentives in the KGEN ecosystem 56:00 What are the goals for KGEN over the next 3-6 months? 1:00:00 What is one perspective you have found most valuable to yourself?
1:02:30

EP:19 ft Ishank Gupta the co-founder of KGeN Foundation 🟩! Discussing: The benefits of travelling, how to navigate the stress of web3, solving distribution and much more! Timestamps: 2:00 What was life like before web3? 7:25 What lessons did you learn from travelling so much? 11:30 How has travelling impacted your perspective for business 14:45 Biggest lessons from working with some of the largest brands in the world. 20:00 What do you look like when hiring? 26:45 How do you navigate such a volatile market on a personal level? 32:55 Story of how KGEN started 40:00 How important is it when selecting which investors to work with. 43:30 What are the missing pieces to solving distribution for web3 gaming? 47:00 How do you re-engage users? 50:00 How does KGEN Chiefs work? 53:00 Aligning incentives in the KGEN ecosystem 56:00 What are the goals for KGEN over the next 3-6 months? 1:00:00 What is one perspective you have found most valuable to yourself?

Caleb

172,615 次观看 • 1 年前